Thermally induced microcracks and mechanical property of composite honeycomb sandwich structure: Experiment and finite element analysis
Bibliographic record
Abstract
Microcracking in composite honeycomb sandwich structure and its effect on mechanical properties are studied in this paper. A methodology is presented to study the extent of mechanical strength degradation of composite sandwich structure, subjected to thermal fatigue. The material under study is used for spacecraft structural applications. The test coupons were exposed to thermal cycling at elevated temperature as high as +150°C inside the oven and cryogenic temperature of −190°C by dipping in liquid nitrogen, which is comparable to the thermal environment experienced by spacecraft structures. After each thermal cycle, coupons were inspected for microcracks under an optical microscope at the cross section. The microcracks were then quantified using parameters like crack length and crack density with increase in the number of cycles. Flatwise tensile test was conducted on the coupons after every 10 thermal cycles, up to 60 cycles, to make a correlation between crack density and mechanical strength. It was observed that by increasing the number of thermal cycles, the crack density increases and the flatwise tensile strength decreases up to a specific number of cycles. Finite element analysis was performed to predict the possible location of microcracks formation and compared with experimental observation. Good correlation was observed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".